ProjektAD01
Agnieszka Domeracka
2021-06-06
Abstract
The world is struggling with COVID-19 epidemic since December 2019. The virus causes severe respiratory complications, which, can lead to patient death. The number of deaths increase sharply with age. However, the young are also at risk. White blood cells are responsible of human immune system. The main task of whit blood cells is to protect the body against infections and diseases. The aim analysis presented below is to investigate the influence of number or percentage of white blood cells group, including neutrophils and lymphocyte. The author analyzed the blood samples of 375 patients from January 10 to February 18, 2020 from the region of Wuhan, China to identify mortality risk on the basis of different white blood cells types percentage in blood.
Libraries list
## R version 4.0.4 (2021-02-15)
## Platform: i386-w64-mingw32/i386 (32-bit)
## Running under: Windows 10 x64 (build 18363)
##
## Matrix products: default
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] caret_6.0-88 lattice_0.20-41 mlbench_2.1-3 ggsci_2.9
## [5] plyr_1.8.6 zoo_1.8-9 dplyr_1.0.5 plotly_4.9.3
## [9] ggplot2_3.3.3 tidyr_1.1.3 knitr_1.32 openxlsx_4.2.3
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.6 lubridate_1.7.10 class_7.3-18
## [4] assertthat_0.2.1 digest_0.6.27 ipred_0.9-11
## [7] foreach_1.5.1 utf8_1.2.1 R6_2.5.0
## [10] stats4_4.0.4 evaluate_0.14 httr_1.4.2
## [13] pillar_1.6.0 rlang_0.4.10 lazyeval_0.2.2
## [16] data.table_1.14.0 jquerylib_0.1.4 rpart_4.1-15
## [19] Matrix_1.3-2 rmarkdown_2.7 splines_4.0.4
## [22] gower_0.2.2 stringr_1.4.0 htmlwidgets_1.5.3
## [25] munsell_0.5.0 compiler_4.0.4 xfun_0.22
## [28] pkgconfig_2.0.3 htmltools_0.5.1.1 nnet_7.3-15
## [31] tidyselect_1.1.0 prodlim_2019.11.13 tibble_3.1.0
## [34] codetools_0.2-18 fansi_0.4.2 viridisLite_0.4.0
## [37] crayon_1.4.1 withr_2.4.1 ModelMetrics_1.2.2.2
## [40] MASS_7.3-53 recipes_0.1.16 grid_4.0.4
## [43] nlme_3.1-152 jsonlite_1.7.2 gtable_0.3.0
## [46] lifecycle_1.0.0 DBI_1.1.1 magrittr_2.0.1
## [49] pROC_1.17.0.1 scales_1.1.1 zip_2.1.1
## [52] stringi_1.5.3 reshape2_1.4.4 timeDate_3043.102
## [55] bslib_0.2.5.1 ellipsis_0.3.1 generics_0.1.0
## [58] vctrs_0.3.7 lava_1.6.9 iterators_1.0.13
## [61] tools_4.0.4 glue_1.4.2 purrr_0.3.4
## [64] survival_3.2-11 yaml_2.2.1 colorspace_2.0-0
## [67] sass_0.4.0## Loading required package: data.table##
## Attaching package: 'data.table'## The following objects are masked from 'package:dplyr':
##
## between, first, lastInput data summary
Dimensions
| x |
|---|
| 6120 |
| 81 |
| Hypersensitive.cardiac.troponinI | hemoglobin | Serum.chloride | Prothrombin.time | procalcitonin | eosinophils(%) | Interleukin.2.receptor | Alkaline.phosphatase | albumin | basophil(%) | Interleukin.10 | Total.bilirubin | Platelet.count | monocytes(%) | antithrombin | Interleukin.8 | indirect.bilirubin | Red.blood.cell.distribution.width | neutrophils(%) | total.protein | Quantification.of.Treponema.pallidum.antibodies | Prothrombin.activity | HBsAg | mean.corpuscular.volume | hematocrit | White.blood.cell.count | Tumor.necrosis.factorα | mean.corpuscular.hemoglobin.concentration | fibrinogen | Interleukin.1β | Urea | lymphocyte.count | PH.value | Red.blood.cell.count | Eosinophil.count | Corrected.calcium | Serum.potassium | glucose | neutrophils.count | Direct.bilirubin | Mean.platelet.volume | ferritin | RBC.distribution.width.SD | Thrombin.time | (%)lymphocyte | HCV.antibody.quantification | D-D.dimer | Total.cholesterol | aspartate.aminotransferase | Uric.acid | HCO3- | calcium | Amino-terminal.brain.natriuretic.peptide.precursor(NT-proBNP) | Lactate.dehydrogenase | platelet.large.cell.ratio | Interleukin.6 | Fibrin.degradation.products | monocytes.count | PLT.distribution.width | globulin | γ-glutamyl.transpeptidase | International.standard.ratio | basophil.count(#) | 2019-nCoV.nucleic.acid.detection | mean.corpuscular.hemoglobin | Activation.of.partial.thromboplastin.time | High.sensitivity.C-reactive.protein | HIV.antibody.quantification | serum.sodium | thrombocytocrit | ESR | glutamic-pyruvic.transaminase | eGFR | creatinine | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min. : 1.9 | Min. : 6.4 | Min. : 71.50 | Min. : 11.50 | Min. : 0.020 | Min. :0.000 | Min. : 61.0 | Min. : 17.00 | Min. :13.60 | Min. :0.00 | Min. : 5.00 | Min. : 2.50 | Min. : -1.0 | Min. : 0.300 | Min. : 20.00 | Min. : 5.000 | Min. : 0.100 | Min. :10.60 | Min. : 1.7 | Min. :31.80 | Min. : 0.020 | Min. : 6.00 | Min. : 0.000 | Min. : 61.60 | Min. :14.50 | Min. : 0.13 | Min. : 4.00 | Min. :286.0 | Min. : 0.500 | Min. : 5.00 | Min. : 0.800 | Min. : 0.000 | Min. :5.000 | Min. : 0.100 | Min. :0.000 | Min. :1.650 | Min. : 2.760 | Min. : 1.000 | Min. : 0.06 | Min. : 1.600 | Min. : 8.50 | Min. : 17.8 | Min. : 31.30 | Min. : 13.00 | Min. : 0.000 | Min. :0.020 | Min. : 0.210 | Min. :0.100 | Min. : 6.00 | Min. : 43.0 | Min. : 6.30 | Min. :1.170 | Min. : 5 | Min. : 110.0 | Min. :11.20 | Min. : 1.500 | Min. : 4.00 | Min. : 0.010 | Min. : 8.00 | Min. :10.10 | Min. : 3.00 | Min. : 0.840 | Min. :0.000 | Min. :-1 | Min. :20.4 | Min. : 21.80 | Min. : 0.10 | Min. :0.05 | Min. :115.4 | Min. :0.010 | Min. : 1.00 | Min. : 5.00 | Min. : 2.00 | Min. : 11.00 | |
| 1st Qu.: 4.4 | 1st Qu.:113.0 | 1st Qu.: 99.05 | 1st Qu.: 13.60 | 1st Qu.: 0.040 | 1st Qu.:0.000 | 1st Qu.: 459.5 | 1st Qu.: 54.00 | 1st Qu.:27.40 | 1st Qu.:0.10 | 1st Qu.: 5.00 | 1st Qu.: 7.40 | 1st Qu.:109.0 | 1st Qu.: 2.800 | 1st Qu.: 74.00 | 1st Qu.: 8.675 | 1st Qu.: 3.800 | 1st Qu.:12.00 | 1st Qu.:65.1 | 1st Qu.:61.00 | 1st Qu.: 0.040 | 1st Qu.: 65.00 | 1st Qu.: 0.000 | 1st Qu.: 86.90 | 1st Qu.:33.50 | 1st Qu.: 4.94 | 1st Qu.: 6.70 | 1st Qu.:333.0 | 1st Qu.: 3.050 | 1st Qu.: 5.00 | 1st Qu.: 4.000 | 1st Qu.: 0.460 | 1st Qu.:6.000 | 1st Qu.: 3.680 | 1st Qu.:0.000 | 1st Qu.:2.270 | 1st Qu.: 3.950 | 1st Qu.: 5.550 | 1st Qu.: 3.09 | 1st Qu.: 3.225 | 1st Qu.:10.10 | 1st Qu.: 377.2 | 1st Qu.: 38.50 | 1st Qu.: 15.60 | 1st Qu.: 3.925 | 1st Qu.:0.040 | 1st Qu.: 0.603 | 1st Qu.:3.010 | 1st Qu.: 19.50 | 1st Qu.: 183.2 | 1st Qu.:21.00 | 1st Qu.:1.980 | 1st Qu.: 150 | 1st Qu.: 218.0 | 1st Qu.:25.60 | 1st Qu.: 4.772 | 1st Qu.: 4.00 | 1st Qu.: 0.270 | 1st Qu.:11.10 | 1st Qu.:29.70 | 1st Qu.: 22.00 | 1st Qu.: 1.030 | 1st Qu.:0.010 | 1st Qu.:-1 | 1st Qu.:29.7 | 1st Qu.: 35.30 | 1st Qu.: 5.70 | 1st Qu.:0.07 | 1st Qu.:137.7 | 1st Qu.:0.150 | 1st Qu.: 14.00 | 1st Qu.: 16.00 | 1st Qu.: 63.58 | 1st Qu.: 58.00 | |
| Median : 20.6 | Median :125.0 | Median :102.10 | Median : 14.80 | Median : 0.100 | Median :0.100 | Median : 676.5 | Median : 69.50 | Median :32.20 | Median :0.20 | Median : 5.90 | Median : 10.70 | Median :178.0 | Median : 5.700 | Median : 86.00 | Median : 16.000 | Median : 5.400 | Median :12.60 | Median :82.4 | Median :65.90 | Median : 0.050 | Median : 81.00 | Median : 0.010 | Median : 90.10 | Median :36.60 | Median : 7.72 | Median : 8.60 | Median :343.0 | Median : 4.120 | Median : 5.00 | Median : 5.985 | Median : 0.800 | Median :6.500 | Median : 4.140 | Median :0.010 | Median :2.360 | Median : 4.410 | Median : 6.990 | Median : 5.85 | Median : 4.800 | Median :10.80 | Median : 711.0 | Median : 40.90 | Median : 16.80 | Median :11.450 | Median :0.060 | Median : 2.155 | Median :3.630 | Median : 27.00 | Median : 243.7 | Median :23.50 | Median :2.080 | Median : 585 | Median : 340.0 | Median :30.90 | Median : 19.265 | Median : 17.90 | Median : 0.410 | Median :12.40 | Median :32.70 | Median : 34.00 | Median : 1.140 | Median :0.010 | Median :-1 | Median :30.9 | Median : 39.20 | Median : 51.50 | Median :0.09 | Median :140.4 | Median :0.210 | Median : 28.00 | Median : 24.00 | Median : 87.90 | Median : 76.00 | |
| Mean : 1223.2 | Mean :123.1 | Mean :103.14 | Mean : 16.68 | Mean : 1.107 | Mean :0.629 | Mean : 907.2 | Mean : 82.47 | Mean :32.01 | Mean :0.21 | Mean : 16.07 | Mean : 16.70 | Mean :184.3 | Mean : 6.155 | Mean : 85.32 | Mean : 83.088 | Mean : 6.889 | Mean :13.07 | Mean :77.6 | Mean :65.30 | Mean : 0.132 | Mean : 78.55 | Mean : 8.306 | Mean : 90.39 | Mean :36.55 | Mean : 15.60 | Mean : 11.58 | Mean :342.8 | Mean : 4.294 | Mean : 6.51 | Mean : 9.589 | Mean : 1.017 | Mean :6.484 | Mean : 9.288 | Mean :0.039 | Mean :2.355 | Mean : 4.509 | Mean : 8.889 | Mean : 7.81 | Mean : 9.887 | Mean :10.91 | Mean : 1379.1 | Mean : 42.44 | Mean : 18.17 | Mean :15.392 | Mean :0.117 | Mean : 7.943 | Mean :3.689 | Mean : 46.53 | Mean : 276.1 | Mean :23.14 | Mean :2.078 | Mean : 3669 | Mean : 474.2 | Mean :31.77 | Mean : 112.308 | Mean : 61.35 | Mean : 0.526 | Mean :13.01 | Mean :33.24 | Mean : 55.34 | Mean : 1.313 | Mean :0.017 | Mean :-1 | Mean :31.0 | Mean : 41.52 | Mean : 76.24 | Mean :0.10 | Mean :141.6 | Mean :0.212 | Mean : 33.69 | Mean : 38.86 | Mean : 81.56 | Mean : 109.93 | |
| 3rd Qu.: 223.8 | 3rd Qu.:137.0 | 3rd Qu.:105.65 | 3rd Qu.: 16.70 | 3rd Qu.: 0.405 | 3rd Qu.:0.800 | 3rd Qu.:1155.5 | 3rd Qu.: 95.00 | 3rd Qu.:36.60 | 3rd Qu.:0.30 | 3rd Qu.: 12.35 | 3rd Qu.: 16.77 | 3rd Qu.:248.0 | 3rd Qu.: 8.600 | 3rd Qu.: 97.00 | 3rd Qu.: 35.200 | 3rd Qu.: 8.000 | 3rd Qu.:13.70 | 3rd Qu.:92.3 | 3rd Qu.:70.45 | 3rd Qu.: 0.070 | 3rd Qu.: 95.00 | 3rd Qu.: 0.010 | 3rd Qu.: 93.90 | 3rd Qu.:39.90 | 3rd Qu.: 12.72 | 3rd Qu.: 11.50 | 3rd Qu.:350.0 | 3rd Qu.: 5.480 | 3rd Qu.: 5.00 | 3rd Qu.:11.400 | 3rd Qu.: 1.310 | 3rd Qu.:7.294 | 3rd Qu.: 4.650 | 3rd Qu.:0.060 | 3rd Qu.:2.440 | 3rd Qu.: 4.870 | 3rd Qu.:10.260 | 3rd Qu.:10.95 | 3rd Qu.: 8.275 | 3rd Qu.:11.50 | 3rd Qu.: 1425.2 | 3rd Qu.: 44.70 | 3rd Qu.: 18.38 | 3rd Qu.:24.975 | 3rd Qu.:0.090 | 3rd Qu.:21.000 | 3rd Qu.:4.265 | 3rd Qu.: 42.00 | 3rd Qu.: 333.8 | 3rd Qu.:25.90 | 3rd Qu.:2.190 | 3rd Qu.: 2625 | 3rd Qu.: 601.8 | 3rd Qu.:37.20 | 3rd Qu.: 60.167 | 3rd Qu.:150.00 | 3rd Qu.: 0.580 | 3rd Qu.:14.30 | 3rd Qu.:36.50 | 3rd Qu.: 58.00 | 3rd Qu.: 1.330 | 3rd Qu.:0.020 | 3rd Qu.:-1 | 3rd Qu.:32.2 | 3rd Qu.: 44.12 | 3rd Qu.:118.50 | 3rd Qu.:0.11 | 3rd Qu.:143.5 | 3rd Qu.:0.270 | 3rd Qu.: 45.50 | 3rd Qu.: 41.00 | 3rd Qu.:103.97 | 3rd Qu.: 98.25 | |
| Max. :50000.0 | Max. :178.0 | Max. :140.40 | Max. :120.00 | Max. :57.170 | Max. :8.600 | Max. :7500.0 | Max. :620.00 | Max. :48.60 | Max. :1.70 | Max. :1000.00 | Max. :505.70 | Max. :558.0 | Max. :53.000 | Max. :136.00 | Max. :6795.000 | Max. :145.100 | Max. :27.10 | Max. :98.9 | Max. :88.70 | Max. :11.950 | Max. :142.00 | Max. :250.000 | Max. :118.90 | Max. :52.30 | Max. :1726.60 | Max. :168.00 | Max. :514.0 | Max. :10.780 | Max. :88.50 | Max. :68.400 | Max. :52.420 | Max. :7.565 | Max. :749.500 | Max. :0.490 | Max. :2.790 | Max. :12.800 | Max. :43.010 | Max. :33.88 | Max. :360.600 | Max. :15.00 | Max. :50000.0 | Max. :113.30 | Max. :161.90 | Max. :60.000 | Max. :2.090 | Max. :60.000 | Max. :7.300 | Max. :1858.00 | Max. :1176.0 | Max. :36.30 | Max. :2.620 | Max. :70000 | Max. :1867.0 | Max. :62.20 | Max. :5000.000 | Max. :190.80 | Max. :39.920 | Max. :25.30 | Max. :50.60 | Max. :732.00 | Max. :13.480 | Max. :0.120 | Max. :-1 | Max. :50.8 | Max. :144.00 | Max. :320.00 | Max. :0.27 | Max. :179.7 | Max. :0.510 | Max. :110.00 | Max. :1600.00 | Max. :224.00 | Max. :1497.00 | |
| NA’s :5613 | NA’s :5145 | NA’s :5145 | NA’s :5458 | NA’s :5661 | NA’s :5163 | NA’s :5852 | NA’s :5190 | NA’s :5186 | NA’s :5163 | NA’s :5853 | NA’s :5190 | NA’s :5163 | NA’s :5162 | NA’s :5790 | NA’s :5852 | NA’s :5214 | NA’s :5197 | NA’s :5163 | NA’s :5189 | NA’s :5841 | NA’s :5461 | NA’s :5841 | NA’s :5163 | NA’s :5163 | NA’s :4993 | NA’s :5852 | NA’s :5163 | NA’s :5554 | NA’s :5852 | NA’s :5184 | NA’s :5163 | NA’s :5736 | NA’s :4993 | NA’s :5163 | NA’s :5206 | NA’s :5140 | NA’s :5345 | NA’s :5163 | NA’s :5190 | NA’s :5258 | NA’s :5837 | NA’s :5197 | NA’s :5554 | NA’s :5162 | NA’s :5841 | NA’s :5490 | NA’s :5189 | NA’s :5185 | NA’s :5186 | NA’s :5186 | NA’s :5141 | NA’s :5645 | NA’s :5186 | NA’s :5258 | NA’s :5848 | NA’s :5790 | NA’s :5163 | NA’s :5258 | NA’s :5190 | NA’s :5190 | NA’s :5461 | NA’s :5163 | NA’s :5619 | NA’s :5163 | NA’s :5552 | NA’s :5383 | NA’s :5842 | NA’s :5145 | NA’s :5258 | NA’s :5737 | NA’s :5189 | NA’s :5184 | NA’s :5184 |
Parameters list:
## [1] "PATIENT_ID"
## [2] "RE_DATE"
## [3] "age"
## [4] "gender"
## [5] "Admission.time"
## [6] "Discharge.time"
## [7] "outcome"
## [8] "Hypersensitive.cardiac.troponinI"
## [9] "hemoglobin"
## [10] "Serum.chloride"
## [11] "Prothrombin.time"
## [12] "procalcitonin"
## [13] "eosinophils(%)"
## [14] "Interleukin.2.receptor"
## [15] "Alkaline.phosphatase"
## [16] "albumin"
## [17] "basophil(%)"
## [18] "Interleukin.10"
## [19] "Total.bilirubin"
## [20] "Platelet.count"
## [21] "monocytes(%)"
## [22] "antithrombin"
## [23] "Interleukin.8"
## [24] "indirect.bilirubin"
## [25] "Red.blood.cell.distribution.width"
## [26] "neutrophils(%)"
## [27] "total.protein"
## [28] "Quantification.of.Treponema.pallidum.antibodies"
## [29] "Prothrombin.activity"
## [30] "HBsAg"
## [31] "mean.corpuscular.volume"
## [32] "hematocrit"
## [33] "White.blood.cell.count"
## [34] "Tumor.necrosis.factor<U+03B1>"
## [35] "mean.corpuscular.hemoglobin.concentration"
## [36] "fibrinogen"
## [37] "Interleukin.1ß"
## [38] "Urea"
## [39] "lymphocyte.count"
## [40] "PH.value"
## [41] "Red.blood.cell.count"
## [42] "Eosinophil.count"
## [43] "Corrected.calcium"
## [44] "Serum.potassium"
## [45] "glucose"
## [46] "neutrophils.count"
## [47] "Direct.bilirubin"
## [48] "Mean.platelet.volume"
## [49] "ferritin"
## [50] "RBC.distribution.width.SD"
## [51] "Thrombin.time"
## [52] "(%)lymphocyte"
## [53] "HCV.antibody.quantification"
## [54] "D-D.dimer"
## [55] "Total.cholesterol"
## [56] "aspartate.aminotransferase"
## [57] "Uric.acid"
## [58] "HCO3-"
## [59] "calcium"
## [60] "Amino-terminal.brain.natriuretic.peptide.precursor(NT-proBNP)"
## [61] "Lactate.dehydrogenase"
## [62] "platelet.large.cell.ratio"
## [63] "Interleukin.6"
## [64] "Fibrin.degradation.products"
## [65] "monocytes.count"
## [66] "PLT.distribution.width"
## [67] "globulin"
## [68] "<U+03B3>-glutamyl.transpeptidase"
## [69] "International.standard.ratio"
## [70] "basophil.count(#)"
## [71] "2019-nCoV.nucleic.acid.detection"
## [72] "mean.corpuscular.hemoglobin"
## [73] "Activation.of.partial.thromboplastin.time"
## [74] "High.sensitivity.C-reactive.protein"
## [75] "HIV.antibody.quantification"
## [76] "serum.sodium"
## [77] "thrombocytocrit"
## [78] "ESR"
## [79] "glutamic-pyruvic.transaminase"
## [80] "eGFR"
## [81] "creatinine"Atributes analysis
Average patients age: 59
The oldest patient: 95
The youngest patient: 18
Number of survived : 201
Number of deaths: 174
**
| Died | Survived | |
|---|---|---|
| Female | 48 | 103 |
| Male | 126 | 98 |
**
Patients information
| gender | averageage | |
|---|---|---|
| Male | Female | 55.17881 |
| Female | Male | 61.28571 |
Blood samples analysis
Notice: Normal percentage is between 10-45%
Notiice: Neutrophils - the most numerous group of white blood cells of the immune system. The task of neutrophils is to protect the body against infections and diseases. The norm for neutrophils is 60-70% of all white blood cells
Male and female, dead and survived in function of age
Data coralations - Pearson method
## Creating predictive models with caret
Data was divided into training and testing where p=0.75
## [1] "Died" "Survived"
Notice: Due to the NA values in blood samples it was not possible to apply any caret model (e.g. RF, parRF, bayesglm)
Summary
The main purpose of the analysis was to investigate the white blood composition of death and survived patients. To analyse the mortality of individual patients three parameters were taken into account: number of white cells in blood, percentage of lymphocytes and percentage of neutrophils. The blood tests results were presented in different graphs. The analysis indicate that for patients who died these three parameters were off the scale. The author tried to create an predictive model to forecasts the mortality of patients. Due to the incomplete blood tests the author was not able to apply any model from Caret library. The author tried to apply models like RF, parRF, bayesglm. However the data was divided into training and testing dataset and the regression chart was made.